Ecoenzymatic stoichiometry of microbial nutrient acquisition in tropical soils

The relative activities of soil enzymes involved in mineralizing organic carbon (C), nitrogen (N), and phosphorus (P) reveal stoichiometric and energetic constraints on microbial biomass growth. Although tropical forests and grasslands are a major component of the global C cycle, the effects of soil nutrient availability on microbial activity and C dynamics in these ecosystems are poorly understood. To explore potential microbial nutrient limitation in relation to enzyme allocation in low latitude ecosystems, we performed a meta-analysis of acid/alkaline phosphatase (AP), β-1,4-glucosidase (BG), and β-1,4-N-acetyl-glucosaminidase (NAG) activities in tropical soils. We found that BG:AP and NAG:AP ratios in tropical soils are significantly lower than those of temperate ecosystems overall. The lowest BG:AP and NAG:AP ratios were associated with old or acid soils, consistent with greater biological phosphorus demand relative to P availability. Additionally, correlations between enzyme activities and mean annual temperature and precipitation suggest some climatic regulation of microbial enzyme allocation in tropical soils. We used the results of our analysis in conjunction with previously published data on soil and biomass C:N:P stoichiometry to parameterize a biogeochemical equilibrium model that relates microbial growth efficiency to extracellular enzyme activity. The model predicts low microbial growth efficiencies in P-limited soils, indicating that P availability may influence C cycling in the highly weathered soils that underlie many tropical ecosystems. Therefore, we suggest that P availability be included in models that simulate microbial enzyme allocation, biomass growth, and C mineralization.     

Caught in the web: Spider web architecture affects prey specialization and spider–prey stoichiometric relationships

Quantitative approaches to predator–prey interactions are central to understanding the structure of food webs and their dynamics. Different predatory strategies may influence the occurrence and strength of trophic interactions likely affecting the rates and magnitudes of energy and nutrient transfer between trophic levels and stoichiometry of predator–prey interactions. Here, we used spider–prey interactions as a model system to investigate whether different spider web architectures—orb, tangle, and sheet‐tangle—affect the composition and diet breadth of spiders and whether these, in turn, influence stoichiometric relationships between spiders and their prey. Our results showed that web architecture partially affects the richness and composition of the prey captured by spiders. Tangle‐web spiders were specialists, capturing a restricted subset of the prey community (primarily Diptera), whereas orb and sheet‐tangle web spiders were generalists, capturing a broader range of prey types. We also observed elemental imbalances between spiders and their prey. In general, spiders had higher requirements for both nitrogen (N) and phosphorus (P) than those provided by their prey even after accounting for prey biomass. Larger P imbalances for tangle‐web spiders than for orb and sheet‐tangle web spiders suggest that trophic specialization may impose strong elemental constraints for these predators unless they display behavioral or physiological mechanisms to cope with nutrient limitation. Our findings suggest that integrating quantitative analysis of species interactions with elemental stoichiometry can help to better understand the occurrence of stoichiometric imbalances in predator–prey interactions.     

Data reconciliation and parameter estimation in flux-balance analysis

Flux blance analysis (FBA) has been shown to be a very effective tool to interpret and predict the metabolism of various microorganisms when the set of available measurements is not sufficient to determine the fluxes within the cell. In this methodology, an underdetermined stoichiometric model is solved using a linear programming (LP) approach. The predictions of FBA models can be improved if noisy measurements are checked for consistency, and these in turn are used to estimate model parameters. In this work, a formal methodology for data reconciliation and parameter estimation with underdetermined stoichiometric models is developed and assessed. The procedure is formulated as a nonlinear optimization problem, where the LP is transformed into a set of nonlinear constraints. However, some of these constraints violate standard regularity conditions, making the direct numerical solution very difficult. Hence, a barrier formulation is used to represent these constraints, and an iterative procedure is defined that allows solving the problem to the desired degree of convergence. This methodology is assessed using a stoichiometric yeast model. The procedure is used for data reconciliation where more reliable estimations of noisy measurements are computed. On the other hand, assuming unknown biomass composition, the procedure is applied for simultaneous data reconciliation and biomass composition estimation. In both cases it is verified that the f measurements required to get unbiased and reliable estimations is reduced if the LP approach is included as additional constraints in the optimization.     

Bistability and oscillations in chemical reaction networks

Bifurcation theory is one of the most widely used approaches for analysis of dynamical behaviour of chemical and biochemical reaction networks. Some of the interesting qualitative behaviour that are analyzed are oscillations and bistability (a situation where a system has at least two coexisting stable equilibria). Both phenomena have been identified as central features of many biological and biochemical systems. This paper, using the theory of stoichiometric network analysis (SNA) and notions from algebraic geometry, presents sufficient conditions for a reaction network to display bifurcations associated with these phenomena. The advantage of these conditions is that they impose fewer algebraic conditions on model parameters than conditions associated with standard bifurcation theorems. To derive the new conditions, a coordinate transformation will be made that will guarantee the existence of branches of positive equilibria in the system. This is particularly useful in mathematical biology, where only positive variable values are considered to be meaningful. The first part of the paper will be an extended introduction to SNA and algebraic geometry-related methods which are used in the coordinate transformation and set up of the theorems. In the second part of the paper we will focus on the derivation of bifurcation conditions using SNA and algebraic geometry. Conditions will be derived for three bifurcations: the saddle-node bifurcation, a simple branching point, both linked to bistability, and a simple Hopf bifurcation. The latter is linked to oscillatory behaviour. The conditions derived are sufficient and they extend earlier results from stoichiometric network analysis as can be found in (Aguda and Clarke in J Chem Phys 87:3461–3470, 1987; Clarke and Jiang in J Chem Phys 99:4464–4476, 1993; Gatermann et al. in J Symb Comput 40:1361–1382, 2005). In these papers some necessary conditions for two of these bifurcations were given. A set of examples will illustrate that algebraic conditions arising from given sufficient bifurcation conditions are not more difficult to interpret nor harder to calculate than those arising from necessary bifurcation conditions. Hence an increasing amount of information is gained at no extra computational cost. The theory can also be used in a second step for a systematic bifurcation analysis of larger reaction networks. We have added a dedication of the paper to K. Gatermann.     

Dynamics of a Producer–Grazer Model Incorporating the Effects of Excess Food Nutrient Content on Grazer’s Growth

Modeling under the framework of ecological stoichiometric allows the investigation of the effects of food quality on food web population dynamics. Recent discoveries in ecological stoichiometry suggest that grazer dynamics are affected by insufficient food nutrient content (low phosphorus (P)/carbon (C) ratio) as well as excess food nutrient content (high P:C). This phenomenon is known as the “stoichiometric knife edge.” While previous models have captured this phenomenon, they do not explicitly track P in the producer or in the media that supports the producer, which brings questions to the validity of their predictions. Here, we extend a Lotka–Volterra-type stoichiometric model by mechanistically deriving and tracking P in the producer and free P in the environment in order to investigate the growth response of Daphnia to algae of varying P:C ratios. Bifurcation analysis and numerical simulations of the full model, that explicitly tracks phosphorus, lead to quantitative different predictions than previous models that neglect to track free nutrients. The full model shows that the fate of the grazer population can be very sensitive to excess nutrient concentrations. Dynamical free nutrient pool seems to induce extreme grazer population density changes when total nutrient is in an intermediate range.     

Quasi-equilibrium reduction in a general class of stoichiometric producer–consumer models

This article compares a general closed nutrient, stoichiometric producer–consumer model to a two-dimensional ‘quasi-equilibrium’ approximation. We demonstrate that the quasi-equilibrium system can be rigorously analysed, resulting in nullcline-based criteria for the local stability of system equilibria and for the non-existence of periodic orbits. These results are applied to a study of the dependence of the reduced system on nutrient and energy enrichment. When energy and nutrient enrichment are considered together, the associated bifurcation structures of the two models are seen to share the same essential qualitative characteristics. However, numerical simulations of the three-dimensional parent model show highly complex domains of the persistence and extinction that by Poincare–Bendixson theory are not possible for the two-dimensional reduction. This complexity demonstrates a major difference between the two models, and suggests potential challenges in the use of either model for predicting the long-term behaviour of real-world systems at specific nutrient and energy levels.     

三江源地区高寒湿地土壤微生物生物量碳氮磷及其化学计量特征

微生物生物量及其化学计量特征是土壤养分循环的重要参数, 对预测气候变化和提高模型准确性及理解陆地生态系统养分循环都起到重要作用。为了明晰高寒生态系统土壤微生物生物量碳(MBC)、微生物生物量氮(MBN)、微生物生物量磷(MBP)浓度及其化学计量特征, 该研究通过在三江源区高寒湿地连续两年的野外调查和室内培养, 分析了50个样点的数据, 探究三江源高寒湿地MBC、MBN、MBP浓度及其化学计量特征, 明确了土壤理化特性和微生物群落特征对其影响。结果表明: (1)三江源高寒湿地MBC、MBN和MBP浓度分别为105.11、3.79和0.78 mmol·kg^-1, MBC:MBN、MBC:MBP、MBN:MBP和MBC:MBN:MBP分别为50.56、184.89、5.42和275:5:1。高寒湿地土壤的MBC浓度显著高于高寒草甸土壤, 而MBN和MBP浓度在高寒湿地和高寒草甸土壤之间没有显著差异; 高寒湿地土壤的MBC:MBN和MBC:MBP显著高于高寒草甸土壤, 而MBN:MBP在高寒湿地和高寒草甸土壤之间差异不显著。(2)土壤理化特性与MBC、MBN和MBP浓度具有显著相关性。土壤含水率与MBC:MBN和MBC:MBP存在显著负相关关系, 而土壤密度与MBC:MBN和MBC:MBP浓度存在显著正相关关系, 土壤全氮含量和MBC:MBP存在显著负相关关系, 而与MBC:MBN的相关关系不显著。土壤理化特性对MBN:MBP的影响不显著。(3)整体而言, 微生物群落结构与MBC、MBN和MBP浓度之间存在显著的相关性。微生物群落结构和MBC:MBN、MBC:MBP的关系是相似的, 总磷脂脂肪酸(PLFA)含量、革兰氏阳性菌、革兰氏阴性菌、细菌、放线菌、丛枝菌根真菌浓度和其他PLFA含量与MBC:MBN和MBC:MBP存在显著负相关关系, 而真菌:细菌与MBC:MBN和MBC:MBP之间存在显著正相关关系, 真菌浓度与MBC:MBN和MBC:MBP之间的相关关系不显著。除丛枝菌根真菌外, MBN:MBP与微生物群落结构均无显著相关关系。     

Quasi-equilibrium reduction in a general class of stoichiometric producer-consumer models

This article compares a general closed nutrient, stoichiometric producer-consumer model to a two-dimensional 'quasi-equilibrium' approximation. We demonstrate that the quasi-equilibrium system can be rigorously analysed, resulting in nullcline-based criteria for the local stability of system equilibria and for the non-existence of periodic orbits. These results are applied to a study of the dependence of the reduced system on nutrient and energy enrichment. When energy and nutrient enrichment are considered together, the associated bifurcation structures of the two models are seen to share the same essential qualitative characteristics. However, numerical simulations of the three-dimensional parent model show highly complex domains of the persistence and extinction that by Poincare-Bendixson theory are not possible for the two-dimensional reduction. This complexity demonstrates a major difference between the two models, and suggests potential challenges in the use of either model for predicting the long-term behaviour of real-world systems at specific nutrient and energy levels.     

Ecological stoichiometry of indirect grazer effects on periphyton nutrient content

Ecological stoichiometry has been successful in enhancing our understanding of trophic interactions between consumer and prey species. Consumer and prey dynamics have been shown to depend on the nutrient composition of the prey relative to the nutrient demand of the consumer. Since most experiments on this topic used a single consumer species, little is known about the validity of stoichiometric constraints on trophic interactions across consumers and ecosystems. We conducted a quantitative meta-analysis on grazer–periphyton experiments to test (1) if benthic grazers have consistent effects on the nutrient composition of their prey, and (2) whether these effects can be aligned to the nutrient stoichiometry of grazer and periphyton, other environmental factors, or experimental constraints. Grazers significantly lowered periphyton C:N and C:P ratios, indicating higher N- and P-content of grazed periphyton across studies. Grazer presence on average increased periphyton N:P ratios, but across studies the effect size did not differ significantly from zero. The sign and strength of grazer effects on periphyton nutrient ratios was strongly dependent on the nutrient content of grazers and their food, but also on grazer biomass, the amount of biomass removal and water column nutrients. Grazer with low P-content tended to reduce periphyton P-content, whereas grazers with high P-content increased periphyton P-content. This result suggests that low grazer P-content can be an indication of physiological P-limitation rather than a result of having relatively low and fixed P-requirements. At the across-system scale of this meta-analysis, predictions from stoichiometric theory are corroborated, but the plasticity of the consumer nutrient composition has to be acknowledged. Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Effects of macrograzers and light on periphyton stoichiometry

Ecological stoichiometry describes the biochemical constraints of trophic interactions emerging from the different nutrient content and nutrient demand of producers and consumers, respectively. Most research on this topic originates from well-mixed pelagic food webs, whereas the idea has received far less attention in spatially structured habitats. Here, we test how light as well as grazing and nutrient regeneration by consumers affects growth and biomass of benthic primary producers. In the first laboratory experiment, we manipulated grazer presence (two different snail species plus ungrazed control), in the second experiment we factorially combined manipulation of grazer presence and light intensity. We monitored snail and periphyton biomass as well as dissolved and particulate nutrients (nitrogen and phosphorus) over time. Grazers significantly reduced algal biomass in both experiments. Grazers affected periphyton nutrient content depending on the prevailing nutrient limitation and their own body stoichiometry. In the nitrogen (N-) limited first experiment, grazers increased N both in the periphyton and in the water column. The effect was stronger for grazers with lower N-content. In the phosphorus (P-) limited second experiment, grazers increased the P-content of the periphyton, but the grazer with lower N-content had additionally positive effects on algal N. Light reduction did not affect periphyton biomass, but increased chlorophyll-, N- and P-content of the periphyton. These experiments revealed that the indirect effects of grazers on periphyton were bound by stoichiometric constraints of nutrient incorporation and excretion.     

Carbon use efficiency of microbial communities: stoichiometry,methodology and modelling

Carbon use efficiency (CUE) is a fundamental parameter for ecological models based on the physiology of microorganisms. CUE determines energy and material flows to higher trophic levels, conversion of plant‐produced carbon into microbial products and rates of ecosystem carbon storage. Thermodynamic calculations support a maximum CUE value of ~ 0.60 (CUE _max). Kinetic and stoichiometric constraints on microbial growth suggest that CUE in multi‐resource limited natural systems should approach ~ 0.3 (CUE _max/2). However, the mean CUE values reported for aquatic and terrestrial ecosystems differ by twofold (~ 0.26 vs. ~ 0.55) because the methods used to estimate CUE in aquatic and terrestrial systems generally differ and soil estimates are less likely to capture the full maintenance costs of community metabolism given the difficulty of measurements in water‐limited environments. Moreover, many simulation models lack adequate representation of energy spilling pathways and stoichiometric constraints on metabolism, which can also lead to overestimates of CUE. We recommend that broad‐scale models use a CUE value of 0.30, unless there is evidence for lower values as a result of pervasive nutrient limitations. Ecosystem models operating at finer scales should consider resource composition, stoichiometric constraints and biomass composition, as well as environmental drivers, to predict the CUE of microbial communities.     

Microbial community dynamics alleviate stoichiometric constraints during litter decay

Under the current paradigm, organic matter decomposition and nutrient cycling rates are a function of the imbalance between substrate and microbial biomass stoichiometry. Challenging this view, we demonstrate that in an individual‐based model, microbial community dynamics alter relative C and N limitation during litter decomposition, leading to a system behaviour not predictable from stoichiometric theory alone. Rather, the dynamics of interacting functional groups lead to an adaptation at the community level, which accelerates nitrogen recycling in litter with high initial C : N ratios and thus alleviates microbial N limitation. This mechanism allows microbial decomposers to overcome large imbalances between resource and biomass stoichiometry without the need to decrease carbon use efficiency (CUE), which is in contrast to predictions of traditional stoichiometric mass balance equations. We conclude that identifying and implementing microbial community‐driven mechanisms in biogeochemical models are necessary for accurately predicting terrestrial C fluxes in response to changing environmental conditions.     

Resilience and local stability in a nutrient-limited resource-consumer system

The “paradox of enrichment” predicts that increasing the growth rate of the resource in a resource-consumer dynamic system, by nutrient enrichment, for example, can lead to local instability of the system—that is, to a Hopf bifurcation. The approach to the Hopf bifurcation is accompanied by a decrease in resilience (rate of return to equilibrium). On the other hand, studies of nutrient cycling in food webs indicate that an increase in the nutrient input rate usually results in increased resilience. Here these two apparently conflicting theoretical results are reconciled with a model of a nutrient-limited resource-consumer system in which the tightly recycled limiting nutrient is explicitly modelled. It is shown that increasing nutrient input may at first lead to increased resilience and that resilience decreases sharply only immediately before the Hopf bifurcation is reached.     

The coupling of biogeochemical cycles of nutrients

For any element which is incorporated into biomass, the biogeochemical cycle of that element in a given ecosystem will be coupled to that of any other element similarly incorporated. The mutual interaction of two such cycles is examined using a simple model in which each cycle is constrained into four compartments. In each cycle the assimilation rate (primary productivity) is related in a non-linear fashion to the two nutrients and to biomass. The interactions are represented by combining a hyperbolic dependence for each nutrient (involving a "Michaelis constant") with a logistic equation governing the dependence of rate on biomass (involving a "carrying capacity"). The response of the model to perturbation (e.g. mobilization of an abiotic reserve) is strongly governed by the values assigned to these constants. The coupled cycles can exhibit positive feed-back with anomalous responses of the steady state and time-dependent solutions may exhibit complex oscillatory behaviour. Both the steady-state sensitivity and the kinetic behaviour of such coupled systems are simplified if the range of atomic ratios permitted by the assimilation process is restricted. It will therefore be of importance to determine under what conditions the assimilation rates for different elements are governed by mass-action effects (Liebig's Law) or by stoichiometric constraints (Redfield ratios).     

Systematic analysis of conservation relations in Escherichia coli genome-scale metabolic network reveals novel growth media

A biochemical species is called producible in a constraints-based metabolic model if a feasible steady-state flux configuration exists that sustains its nonzero concentration during growth. Extreme semipositive conservation relations (ESCRs) are the simplest semipositive linear combinations of species concentrations that are invariant to all metabolic flux configurations. In this article, we outline a fundamental relationship between the ESCRs of a metabolic network and the producibility of a biochemical species under a nutrient media. We exploit this relationship in an algorithm that systematically enumerates all minimal nutrient sets that render an objective species weakly producible (i.e., producible in the absence of thermodynamic constraints) through a simple traversal of ESCRs. We apply our results to a recent genome scale model of Escherichia coli metabolism, in which we traverse the 51 anhydrous ESCRs of the metabolic network to determine all 928 minimal aqueous nutrient media that render biomass weakly producible. Applying irreversibility constraints, we find 287 of these 928 nutrient sets to be thermodynamically feasible. We also find that an additional 365 of these nutrient sets are thermodynamically feasible in the presence of oxygen. Since biomass producibility is commonly used as a surrogate for growth in genome scale metabolic models, our results represent testable hypotheses of alternate growth media derived from in silico analysis of the E. coli genome scale metabolic network.     

Genome-scale metabolic modelling when changes in environmental conditions affect biomass composition

Genome-scale metabolic modeling is an important tool in the study of metabolism by enhancing the collation of knowledge, interpretation of data, and prediction of metabolic capabilities. A frequent assumption in the use of genome-scale models is that the in vivo organism is evolved for optimal growth, where growth is represented by flux through a biomass objective function (BOF). While the specific composition of the BOF is crucial, its formulation is often inherited from similar organisms due to the experimental challenges associated with its proper determination.A cell’s macro-molecular composition is not fixed and it responds to changes in environmental conditions. As a consequence, initiatives for the high-fidelity determination of cellular biomass composition have been launched. Thus, there is a need for a mathematical and computational framework capable of using multiple measurements of cellular biomass composition in different environments. Here, we propose two different computational approaches for directly addressing this challenge: Biomass Trade-off Weighting (BTW) and Higher-dimensional-plane InterPolation (HIP).In lieu of experimental data on biomass composition-variation in response to changing nutrient environment, we assess the properties of BTW and HIP using three hypothetical, yet biologically plausible, BOFs for the Escherichia coli genome-scale metabolic model iML1515. We find that the BTW and HIP formulations have a significant impact on model performance and phenotypes. Furthermore, the BTW method generates larger growth rates in all environments when compared to HIP. Using acetate secretion and the respiratory quotient as proxies for phenotypic changes, we find marked differences between the methods as HIP generates BOFs more similar to a reference BOF than BTW. We conclude that the presented methods constitute a conceptual step in developing genome-scale metabolic modelling approaches capable of addressing the inherent dependence of cellular biomass composition on nutrient environments.     

Recent advances in ecological stoichiometry: insights for population and community ecology

Conventional theories of population and community dynamics are based on a single currency such as number of individuals, biomass, carbon or energy. However, organisms are constructed of multiple elements and often require them (in particular carbon, phosphorus and nitrogen) in different ratios than provided by their resources; this mismatch may constrain the net transfer of energy and elements through trophic levels. Ecological stoichiometry, the study of the balance of elements in ecological processes, offers a framework for exploring ecological effects of such constraints. We review recent theoretical and empirical studies that have considered how stoichiometry may affect population and community dynamics. These studies show that stoichiometric constraints can affect several properties of populations (e.g. stability, oscillations, consumer extinction) and communities (e.g. coexistence of competitors, competitive interactions between different guilds). We highlight gaps in general knowledge and focus on areas of population and community ecology where incorporation of stoichiometric constraints may be particularly fruitful, such as studies of demographic bottlenecks, spatial processes, and multi-species interactions. Finally, we suggest promising directions for new research by recommending potential study systems (terrestrial insects, detritivory-based webs, soil communities) to improve our understanding of populations and communities. Our conclusion is that a better integration of stoichiometric principles and other theoretical approaches in ecology may allow for a richer understanding of both population and community structure and dynamics.     

鄱阳湖湿地两种优势植物叶片C、N、P动态特征

2011年2—6月在鄱阳湖南矶湿地国家级自然保护区逐月测定了灰化苔草(Carex cinerascens)、南荻(Triarrhena lutarioriparia)叶片C、N、P含量及其地上生物量,以阐明鄱阳湖湿地优势植物C、N、P含量及化学计量比动态特征与控制因子,探讨湿地养分利用与限制状况。结果表明：1）两种优势植物叶有机碳含量变化范围分别为365.3—386.6 mg/g和352.6—393.2 mg/g,平均值(?标准差)分别为(375.5?17.4) mg/g和(371.7?12.5) mg/g;叶N含量分别为6.96—17.59 mg/g和5.50—20.68 mg/g,平均值分别为(11.35?1.40) mg/g和(11.54?0.84) mg/g;叶P含量变化范围为0.65—2.14 mg/g和0.57—2.25 mg/g,平均含量为(1.56?0.69) mg/g和(1.55?0.68) mg/g。两种植物C:N、C:P、N:P平均值分别为37.65、413.60、9.62和41.05、410.29、9.57,C、N、P及其化学计量比种间差异不显著(P>0.05)。2）气温与地上生物量是N、P及其化学计量比季节变化的主要控制因子,气温和生物量对两种优势植物叶片氮、磷含量的影响要高于对叶有机碳含量的影响。3）植物C:N、C:P与地上生物量变化趋势基本一致,显示N、P养分利用效率随植物的快速生长而提高;根据两种优势植物及土壤N、P含量与化学计量比来判断,研究区植物更多地受氮限制。     

Modelling the Stoichiometric Regulation of C-Rich Toxins in Marine Dinoflagellates

Toxin production in marine microalgae was previously shown to be tightly coupled with cellular stoichiometry. The highest values of cellular toxin are in fact mainly associated with a high carbon to nutrient cellular ratio. In particular, the cellular accumulation of C-rich toxins (i.e., with C:N > 6.6) can be stimulated by both N and P deficiency. Dinoflagellates are the main producers of C-rich toxins and may represent a serious threat for human health and the marine ecosystem. As such, the development of a numerical model able to predict how toxin production is stimulated by nutrient supply/deficiency is of primary utility for both scientific and management purposes. In this work we have developed a mechanistic model describing the stoichiometric regulation of C-rich toxins in marine dinoflagellates. To this purpose, a new formulation describing toxin production and fate was embedded in the European Regional Seas Ecosystem Model (ERSEM), here simplified to describe a monospecific batch culture. Toxin production was assumed to be composed by two distinct additive terms; the first is a constant fraction of algal production and is assumed to take place at any physiological conditions. The second term is assumed to be dependent on algal biomass and to be stimulated by internal nutrient deficiency. By using these assumptions, the model reproduced the concentrations and temporal evolution of toxins observed in cultures of Ostreopsis cf. ovata, a benthic/epiphytic dinoflagellate producing C-rich toxins named ovatoxins. The analysis of simulations and their comparison with experimental data provided a conceptual model linking toxin production and nutritional status in this species. The model was also qualitatively validated by using independent literature data, and the results indicate that our formulation can be also used to simulate toxin dynamics in other dinoflagellates. Our model represents an important step towards the simulation and prediction of marine algal toxicity.     

Ecoenzymatic Stoichiometry in Relation to Productivity for Freshwater Biofilm and Plankton Communities

The degradation of detrital organic matter and assimilation of carbon (C), nitrogen (N), and phosphorus (P) by heterotrophic microbial communities is mediated by enzymes released into the environment (ecoenzymes). For the attached microbial communities of soils and freshwater sediments, the activities of β-glucosidase, β-N-acetylglucosaminidase, leucine aminopeptidase, and phosphatase show consistent stoichiometric patterns. To determine whether similar constraints apply to planktonic communities, we assembled data from nine studies that include measurements of these enzyme activities along with microbial productivity. By normalizing enzyme activity to productivity, we directly compared the ecoenzymatic stoichiometry of aquatic biofilm and bacterioplankton communities. The relationships between β-glucosidase and α-glucosidase and β-glucosidase and β-N-acetylglucosaminidase were statistically indistinguishable for the two community types, while the relationships between β-glucosidase and phosphatase and β-glucosidase and leucine aminopeptidase significantly differed. For β-glucosidase vs. phosphatase, the differences in slope (biofilm 0.65, plankton 1.05) corresponded with differences in the mean elemental C:P ratio of microbial biomass (60 and 106, respectively). For β-glucosidase vs. leucine aminopeptidase, differences in slope (0.80 and 1.02) did not correspond to differences in the mean elemental C:N of biomass (8.6 and 6.6). β-N-Acetylglucosaminidase activity in biofilms was significantly greater than that of plankton, suggesting that aminosaccharides were a relatively more important N source for biofilms, perhaps because fungi are more abundant. The slopes of β-glucosidase vs. (β-N-acetylglucosaminidase + leucine aminopeptidase) regressions (biofilm 1.07, plankton 0.94) corresponded more closely to the estimated difference in mean biomass C:N. Despite major differences in physical structure and trophic organization, biofilm and plankton communities have similar ecoenzymatic stoichiometry in relation to productivity and biomass composition. These relationships can be integrated into the stoichiometric and metabolic theories of ecology and used to analyze community metabolism in relation to resource constraints.